The disentangling of theory calculations from the fit to data
allows us to face with awareness and devoted attention
problems specific to one of the two heterogeneous worlds.
For example, tensions originating from mutual experimental inconsistencies
(such as those seen in Ref. [1]})
become evident
and can be addressed before and independently of the comparison to theory,
without affecting the judgment of how well one or the other model describes the data.
Most importantly,
while the fit results only represent the data with their well defined and statistically-interpretable uncertainties,
they can be confronted simultaneously to different models or multiple variants of the theory,
the best way to appreciate the elusive concept of theory uncertainty.
Instead, when model calculations are embedded in the fit,
the quantification of theory uncertainties is either neglected or, in the best case, chosen rather arbitrarily
(as in Ref. [2]}),
possibly leading to subjective fit results, not amenable to rigorous interpretations.
Therefore, it is difficult to decide how well a model describes the data,
since the goodness of the global fit
(expressed by the \(\chi ^2\) )
has no statistical meaning when part of the uncertainties are lacking or are arbitrary.
